Improving End-of-Life Care for Nursing Home Residents Using an Interprofessional Approach
Bibliographic record
Abstract
Interprofessional collaboration enhances quality end-of-life care leading to a dignified death. Hospice care uses an interdisciplinary approach to optimize quality of life and mitigate impacts of serious illness. Interventions to improve hospice care delivery have been proven to be effective, but little is known about nursing home staff preparedness, implementation of hospice education, and interprofessional communication. Research is limited on how hospice care can be implemented into the nursing home setting. The purpose of this study was to determine if education combined with a communication tool improved nursing home staff knowledge and improved communication with the hospice team. The descriptive study invited participants to take a preseminar and postseminar survey to assess end-of-life preparedness in terms of willingness, capability, and resilience. A communication tool was implemented to measure collaboration with the hospice team over 3 months. The results from this study suggest education combined with interprofessional communication improves end-of-life care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".